Generalized geometry-based optimal power control in wireless networks

Geometry-based optimal power control was proposed in [14] to transform the power-control problem to a new geometrical problem on the position relationship between a line and some points. This scheme provides a novel visual perspective and lowers the complexity of optimization. We generalize this scheme to a larger class of power-control optimization problems so as to maximize the network utility with multiple average and peak power constraints in wireless networks. To facilitate the handling of the geometrical model, we define a subset of geometrical models with specified characteristics, called a regular geometrical model, and derive the type of power-control problems eligible for the regular geometrical model. For such a type of problems, two strategies are proposed for the construction of the regular geometrical model. Utilizing geometrical properties, we propose a novel geometry-based optimization scheme for the general power-control problem. Its computational complexity is significantly lower than the conventional algorithms. We also provide a further discussion on irregular geometrical model cases. Finally, we provide two examples of deploying the proposed geometry-based power-control scheme.

[1]  Wenbo Wang,et al.  Distributed Resource Allocation Based on Queue Balancing in Multihop Cognitive Radio Networks , 2012, IEEE/ACM Transactions on Networking.

[2]  Leandros Tassiulas,et al.  A Simple Rate Control Algorithm for Maximizing Total User Utility. , 2001, INFOCOM 2001.

[3]  David J. Goodman,et al.  Power control for wireless data , 2000, IEEE Wirel. Commun..

[4]  David Tse,et al.  Multiaccess Fading Channels-Part I: Polymatroid Structure, Optimal Resource Allocation and Throughput Capacities , 1998, IEEE Trans. Inf. Theory.

[5]  Ronald L. Rivest,et al.  Introduction to Algorithms, third edition , 2009 .

[6]  Wei Yu,et al.  Transmitter Optimization for the Multi-Antenna Downlink With Per-Antenna Power Constraints , 2007, IEEE Transactions on Signal Processing.

[7]  Andrea J. Goldsmith,et al.  On the duality of Gaussian multiple-access and broadcast channels , 2002, IEEE Transactions on Information Theory.

[8]  Khaled Ben Letaief,et al.  Multiuser OFDM with adaptive subcarrier, bit, and power allocation , 1999, IEEE J. Sel. Areas Commun..

[9]  Gerard J. Foschini,et al.  Layered space-time architecture for wireless communication in a fading environment when using multi-element antennas , 1996, Bell Labs Technical Journal.

[10]  Roy D. Yates,et al.  A Framework for Uplink Power Control in Cellular Radio Systems , 1995, IEEE J. Sel. Areas Commun..

[11]  Jens Zander,et al.  Performance of optimum transmitter power control in cellular radio systems , 1992 .

[12]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[13]  Holger Boche,et al.  Solution of the multiuser downlink beamforming problem with individual SINR constraints , 2004, IEEE Transactions on Vehicular Technology.

[14]  Wenbo Wang,et al.  Optimal Power Control Under Interference Temperature Constraints in Cognitive Radio Network , 2007, 2007 IEEE Wireless Communications and Networking Conference.

[15]  Jack M. Holtzman,et al.  Analysis of a simple successive interference cancellation scheme in a DS/CDMA system , 1994, IEEE J. Sel. Areas Commun..

[16]  Chi Wan Sung,et al.  A generalized framework for distributed power control in wireless networks , 2005, IEEE Trans. Inf. Theory.

[17]  Mung Chiang,et al.  Power Control in Wireless Cellular Networks , 2008, Found. Trends Netw..

[18]  Wenbo Wang,et al.  An uplink resource allocation scheme for OFDMA-based cognitive radio networks , 2009, Int. J. Commun. Syst..

[19]  Chaohuang Zeng,et al.  Efficient water-filling algorithms for a Gaussian multiaccess channel with ISI , 2000, Vehicular Technology Conference Fall 2000. IEEE VTS Fall VTC2000. 52nd Vehicular Technology Conference (Cat. No.00CH37152).

[20]  Wenbo Wang,et al.  Geometry-based optimal power control of fading multiple access channels for maximum sum-rate in cognitive radio networks , 2010, IEEE Transactions on Wireless Communications.

[21]  T. L. Saaty The Number of Vertices of a Polyhedron , 1955 .